Charging pile intelligent information push and management platform based on artificial intelligence

Abstract

The present invention discloses an intelligent information push and management platform for charging piles based on artificial intelligence. The present invention relates to the technical field of charging piles and solves the problem that the operating temperature of the charging piles can be regulated but the charging rate cannot be fully guaranteed, thereby prolonging the corresponding charging time. The present invention monitors the temperature parameters of the charging piles and adjusts the charging parameters in real time based on the specific values ​​monitored. The relevant values ​​are analyzed in sequence and the range of the charging parameters is gradually reduced, thereby locking the best optimal charging parameter interval. Not only the charging rate can be guaranteed, but also the charging temperature of the corresponding charging pile will not exceed the standard, thereby ensuring the overall charging effect of the charging pile. Based on the relevant changes in the corresponding optimal charging parameter interval, the status of the charging pile is evaluated and analyzed, thereby facilitating the corresponding management party to timely understand the relevant information of the corresponding charging pile and ensuring the relevant management effect of the management platform.

Description

Technical Field

[0001] The present invention relates to the technical field of charging piles, and in particular to an intelligent information push and management platform for charging piles based on artificial intelligence. Background Art

[0002] A charging pile is a device that replenishes power for electric vehicles. Its function is similar to that of a gas pump in a gas station. It can be fixed on the ground or on a wall and installed in public buildings (charging stations, shopping malls, public parking lots, etc.) and residential parking lots. It can charge various types of electric vehicles according to the adjusted voltage and current.

[0003] The application with publication number CN116894659A discloses a charging pile intelligent operation and maintenance management method, system, computer equipment and storage medium, the method comprising: obtaining the charging pile historical operation and maintenance data and the charging pile rated information and / or preset information, and constructing a charging pile fault warning model based on the charging pile historical operation and maintenance data, the charging pile rated information and / or preset information; obtaining the target charging pile operation and maintenance data, and parsing and processing the target charging pile operation and maintenance data through preset parsing rules; inputting the parsed data into the charging pile fault warning model for fault detection; when a fault is detected in the target charging pile, obtaining the fault information, and outputting the fault analysis and processing strategy according to the fault information; generating a maintenance work order according to the fault information, and dispatching it to the maintenance party; obtaining the maintenance feedback corresponding to the maintenance work order, so as to evaluate the service of the maintenance party, and adjusting the dispatching process of the maintenance work order based on the service evaluation. The present invention can systematically improve the charging pile management capability.

[0004] During the intelligent management of the charging pile, when the temperature of the charging pile itself exceeds certain parameters, the charging power is directly reduced to cool the charging pile, so that the charging pile can always operate at a relatively stable temperature. However, although this method can regulate the operating temperature of the charging pile, it cannot fully guarantee the charging rate, which will extend the corresponding charging time and affect the overall charging pile management effect. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent information push and management platform for charging piles based on artificial intelligence, which solves the problem of regulating the operating temperature of the charging piles, but cannot fully guarantee the charging rate, thereby prolonging the corresponding charging time.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent information push and management platform for charging piles based on artificial intelligence, comprising:

[0007] The data monitoring center monitors the charging parameters and temperature parameters of the charging pile in real time;

[0008] The data analysis center performs numerical analysis on the temperature parameters monitored in real time to determine whether the temperature parameters exceed the standard. Based on the results, the charging parameters are changed in real time through the interconnected control center. Based on the real-time analysis results, the optimal charging parameter range is determined and transmitted to the database, including:

[0009] The real-time monitored temperature parameter is calibrated as W i , where i represents different moments, identifying its temperature parameter W i Whether it exceeds the preset temperature Y1, where Y1 is the preset value. i When ≥Y1, a parameter reduction signal is generated and transmitted to the control center;

[0010] If W i When <Y1, obtain the temperature value Sz at the moment before this moment and identify (W i -Sz) whether it satisfies: (W i -Sz) ≥ Y2, where Y2 is the preset value. If it is satisfied, a parameter reduction signal is generated and transmitted to the control center. If (W i -Sz) does not satisfy: (W i -Sz) ≥ Y2, continue monitoring;

[0011] Based on the determined parameter reduction signal, the control center reduces the charging parameter until the temperature parameter is reduced, and then stops, and determines the reduced related parameter G, and controls the charging parameter to climb again, and the climbing value is (G-X1), where X1 is the preset value, and monitors whether the temperature exceeds the standard. If it exceeds the standard, it will be reduced again until the temperature drops, and then the charging parameter will be controlled to climb again (G-2X1). After multiple adjustments, it stops when the climbing temperature does not exceed the judgment standard:

[0012] Record the charging parameter D1 before adjustment and the charging parameter D2 after adjustment, and use [D1, D2] as the optimal charging parameter interval for the charging pile in this working environment. The control center will then charge based on this optimal charging parameter interval and transmit this optimal charging parameter interval to the database for storage;

[0013] The push center determines and displays the corresponding remaining charging time based on the determined optimal charging parameter range and the remaining capacity of the corresponding battery to be charged, including:

[0014] The confirmed remaining capacity to be charged is calibrated as R, and the fastest charging time T2 is determined based on R÷D2=T2, and the slowest charging time T1 is determined based on R÷D1=T1;

[0015] The relevant data analysis end performs numerical analysis on the optimal charging parameter ranges at different stages stored in the database, determines the change curve of the relevant numerical values ​​based on the relevant changes in the maximum and minimum values, and performs a comprehensive analysis of the change curve to determine the relevant status of the charging pile.

[0016] Preferably, the database stores the optimal charging parameter intervals determined in different stages, and sorts the optimal charging parameter intervals according to the order of storage time.

[0017] Preferably, the relevant data analysis end determines the change curve of the relevant value in a specific manner including:

[0018] Arrange the maximum and minimum values ​​of the optimal charging parameter intervals in different stages in chronological order, construct a two-dimensional coordinate system with different stages as horizontal coordinate axes and corresponding charging parameters as vertical coordinate axes, and then determine the corresponding points in the coordinate system with different maximum and minimum values ​​corresponding to different stages, interconnect the corresponding points, and determine the maximum value change curve and the minimum value change curve; including:

[0019] Determine the relevant vertical line of the corresponding points at the same stage between the two curves. The relevant vertical line is the connecting line of the corresponding points at the same stage. Determine the distance value of the relevant vertical line, which is calibrated as JL k , where k represents different stages, and the maximum value of the corresponding stage is marked as ZD k , the minimum value of the corresponding stage is marked as ZX k , where k = 1, 2, ..., n, n represents the total number of the corresponding stages;

[0020] Using HB j =(JL j -JL j-1 )+(ZD j -ZD j-1 )+(ZX j -ZX j-1 ) Determine the combined value HB j , where j∈(2,n), if the HB generated at different stages j <0, assign 1, if HB j When ≥0, assign a value of 2;

[0021] Confirm the relevant assignments of several different stages in turn, and determine the proportion of assignment 1 ZB1 and the proportion of assignment 2 ZB2, where ZB1 = the total number of assignments 1 ÷ the total number of relevant assignments, and ZB2 = the total number of assignments 2 ÷ the total number of relevant assignments;

[0022] If ZB1>2×ZB2, a status decline signal is generated and directly displayed in the management terminal of the administrator; if the proportion ZB1 of the assignment 1 and the proportion ZB2 of the assignment 2 do not satisfy: ZB1>2×ZB2, no processing signal is generated.

[0023] The present invention provides an intelligent information push and management platform for charging piles based on artificial intelligence. Compared with the prior art, it has the following beneficial effects:

[0024] The present invention monitors the temperature parameters of the charging pile, adjusts the charging parameters in real time based on the specific values ​​monitored, analyzes the relevant values ​​in sequence, and gradually reduces the range of the charging parameters, thereby locking the best charging parameter interval, which can not only ensure the charging rate, but also ensure that the charging temperature of the corresponding charging pile will not exceed the standard, thereby ensuring the overall charging effect of the charging pile;

[0025] Based on the corresponding optimal charging parameter range generated by the same charging pile at different stages and the relevant changes in the corresponding numerical values, it is determined whether the charging parameter range corresponding to the charging pile is gradually getting smaller or smaller, so as to conduct a status assessment and analysis of the charging pile. This makes it convenient for the corresponding management party to promptly understand the relevant information of the corresponding charging pile and perform maintenance in a timely manner to ensure the relevant management effect of this management platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0027] Figure 2 It is a plane schematic diagram of the corresponding parameter change curve of the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] Embodiment 1

[0030] See also Figure 1 ,This application provides an intelligent information push and management platform for charging piles based on artificial intelligence, including a data monitoring center, a data analysis center, a control center, a database, a related data analysis terminal and a push center;

[0031] The data monitoring center is electrically connected to the input node of the data analysis center, and the data analysis center is electrically connected to the input nodes of the database, the control center and the push center respectively, and the database is electrically connected to the input nodes of the relevant data analysis terminals;

[0032] The data monitoring center monitors the charging parameters and temperature parameters of the charging pile in real time, and transmits the relevant parameters monitored in real time to the data analysis center. The temperature parameters are obtained by sensors set in the designated area inside the charging pile. The charging parameters are linked to the output parameters of the charging pile and can be directly obtained.

[0033] The data analysis center conducts numerical analysis on the temperature parameters monitored in real time to determine whether the temperature parameters exceed the standard. Based on the determination results, the control center changes the charging parameters in real time. Based on the real-time analysis results, the optimal charging parameter range is determined. Specifically, during the charging process of the charging pile, the temperature of the corresponding charging components inside will rise. Due to the influence of the external ambient temperature, the temperature of the charging pile will exceed the standard during the charging process. If this charging parameter is used for a long time, the charging pile itself will have a safety risk. Therefore, it is necessary to adjust the charging parameters to ensure that the charging temperature of the charging pile does not exceed the standard.

[0034] The specific methods for determination include:

[0035] The real-time monitored temperature parameter is calibrated as W i , where i represents different moments, identifying its temperature parameter W i Whether it exceeds the preset temperature Y1 (where Y1 is the preset value and Y1 is lower than the standard warning temperature. When Y1 is reached, an alarm is required to avoid exceeding the standard warning temperature). If W i When ≥Y1, a parameter reduction signal is generated and transmitted to the control center;

[0036] If W i When <Y1, obtain the temperature value Sz at the moment before this moment and identify (W i -Sz) whether it satisfies: (W i -Sz) ≥ Y2, where Y2 is the preset value, indicating that the temperature rises too fast, which poses a certain safety risk. The specific value is determined by the operator based on experience. If it is satisfied, a parameter reduction signal is generated and transmitted to the control center. If it is not satisfied, monitoring continues;

[0037] The control center, based on the determined parameter reduction signal, reduces the charging parameter until the temperature parameter is reduced, and determines the reduced related parameter G (the original charging parameter is C1, which is adjusted to C2 after reduction, so the generated related parameter G=(C1-C2), and controls the charging parameter to climb again, and its climbing value is (G-X1), where X1 is a preset value, and its specific value is determined by the operator based on experience, and monitors whether the temperature exceeds the standard. If it exceeds the standard, it will be reduced again until the temperature drops, and then the charging parameter is controlled to climb again (G-2X1). After multiple adjustments, it stops when the climbing temperature does not exceed the judgment standard (that is, it does not exceed Y1, or its change trend does not exceed Y2):

[0038] Record the charging parameter D1 before adjustment and the charging parameter D2 after adjustment, and use [D1, D2] as the optimal charging parameter interval for the charging pile in this working environment. The control center will then charge based on this optimal charging parameter interval and transmit this optimal charging parameter interval to the database for storage;

[0039] Specifically, the original charging parameter is set to 100. Under this charging parameter state, its temperature parameter exceeds Y1, so the charging parameter is reduced. When the temperature parameter begins to decrease, its charging parameter is 80, and the generated related parameter G=20. The subsequent change parameter is determined in G, where X1 takes the value of 1, then it climbs. One type of climbing parameter is: 80+(G-1), that is, 80+(20-1)=99. Charging is performed with a charging parameter value of 99, and then it is reduced again. When it is reduced to 80, it is charged at 98, and so on. The range of charging parameters is gradually reduced, thereby locking the best optimal charging parameter range, which can not only ensure the charging rate, but also ensure that the charging temperature of the corresponding charging pile will not exceed the standard, thereby ensuring the overall charging effect of the charging pile.

[0040] Embodiment 2

[0041] Compared with the above embodiment, this embodiment mainly focuses on the corresponding time confirmation process, and pushes the confirmed charging completion time through the push center, and the external charging personnel can view the corresponding charging completion time in real time based on the corresponding APP end;

[0042] The push center determines the corresponding remaining charging time based on the determined optimal charging parameter interval [D1, D2] and the remaining capacity of the corresponding battery to be charged, and displays the determined remaining charging time in the external APP. Specifically, during the charging process, the charging pile monitors the current state of charge (SOC), current and other parameters of the battery, and based on the corresponding parameters, the corresponding remaining charging time can be determined.

[0043] The determination methods include:

[0044] The confirmed remaining capacity to be charged is calibrated as R, and the fastest full charging time T2 is determined based on R÷D2=T2, and the slowest full charging time T1 is determined based on R÷D1=T1. Therefore, based on the full charging time T1 and T2, it can be directly displayed. Based on such parameters, external personnel can understand the corresponding subsequent charging time in real time.

[0045] Embodiment 3

[0046] In the specific implementation process of this embodiment, compared with the above embodiment, this embodiment mainly analyzes the optimal charging parameter intervals corresponding to different stages to identify the specific operating status of the charging pile, and determines the identification signal according to the identification result, so as to display it, so that the management party can understand the relevant status of the corresponding charging pile in time;

[0047] The database stores the optimal charging parameter intervals determined at different stages, and sorts the optimal charging parameter intervals according to the order of storage time;

[0048] The relevant data analysis end performs numerical analysis on the optimal charging parameter intervals at different stages stored in the database, determines the change curve of the relevant numerical values ​​according to the relevant changes of the maximum value and the minimum value, and performs a comprehensive analysis on the change curve to determine the relevant state of the charging pile. The specific methods of performing the comprehensive analysis include:

[0049] Arrange the maximum and minimum values ​​of the optimal charging parameter intervals in different stages in chronological order, construct a two-dimensional coordinate system with different stages as the horizontal coordinate axis and the corresponding charging parameters as the vertical coordinate axis, and then determine the corresponding points in the coordinate system with the different maximum and minimum values ​​corresponding to different stages, interconnect the corresponding points, and determine their maximum value change curve and minimum value change curve;

[0050] Combination Figure 2 , determine the relevant vertical line of the corresponding points at the same stage between the two curves, the relevant vertical line is the connecting line of the corresponding points at the same stage, determine the distance value of the relevant vertical line, calibrated as JL k , where k represents different stages, and the maximum value of the corresponding stage is marked as ZD k , the minimum value of the corresponding stage is marked as ZX k , where k = 1, 2, ..., n, n represents the total number of the corresponding stages;

[0051] Using HB j =(JL j -JL j-1 )+(ZD j -ZDj-1 )+(ZX j -ZX j-1 ) Determine the combined value HB j , where j∈(2,n), if the HB generated at different stages j <0, assign 1, if HB j When ≥0, assign a value of 2;

[0052] Confirm the relevant assignments of several different stages in turn, and determine the proportion of assignment 1 ZB1 and the proportion of assignment 2 ZB2, where ZB1 = the total number of assignments 1 ÷ the total number of relevant assignments, and ZB2 = the total number of assignments 2 ÷ the total number of relevant assignments;

[0053] If ZB1>2×ZB2, a status downgrade signal is generated and directly displayed in the management terminal. Otherwise, no processing signal is generated;

[0054] Specifically, the database stores five groups of optimal charging parameter intervals at different stages, namely: A[80, 100], B[82, 98], C[84, 94], D[86, 92] and E[89, 91], wherein the distance value of the relevant vertical line generated by A is 20, the distance value of the relevant vertical line generated by B is 16, the distance value of the relevant vertical line generated by C is 10, the distance value of the relevant vertical line generated by D is 6, and the distance value of the relevant vertical line generated by E is 2;

[0055] According to the above processing method, the corresponding merged value generated from AB is -4, where -4 < 0, so the value is assigned 1. Similarly, the corresponding merged value generated in the BC stage is -8, which is also less than 0, and the value is also assigned 1. Similarly, the subsequent merged values ​​are confirmed in sequence. The confirmed subsequent two groups of assignments are 1 and 1 respectively, so the generated assignment is 1111, and the assignment 1 accounts for the largest proportion, and it also satisfies: ZB1>2×ZB2, then the corresponding state decline signal is generated;

[0056] Based on the corresponding parameter range generated by the same charging pile, the status of the charging pile is evaluated and analyzed, so that the corresponding management party can timely understand the relevant information of the corresponding charging pile and perform maintenance in time to ensure the relevant management effect of this management platform.

[0057] Embodiment 4

[0058] The specific implementation process of this embodiment includes all the implementation processes of the above three groups of embodiments.

[0059] Some of the data in the above formulas are numerically calculated by removing their dimensions. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0060] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An AI-based charging pile intelligent information push and management platform, characterized by: include: The data monitoring center monitors the charging parameters and temperature parameters of the charging pile in real time; The data analysis center performs numerical analysis on the temperature parameters monitored in real time to determine whether the temperature parameters exceed the standard. Based on the results, the charging parameters are changed in real time through the interconnected control center. Based on the real-time analysis results, the optimal charging parameter range is determined and transmitted to the database, including: The real-time monitored temperature parameter is calibrated as W i , where i represents different moments, identifying its temperature parameter W i Whether it exceeds the preset temperature Y1, where Y1 is the preset value. i When ≥Y1, a parameter reduction signal is generated and transmitted to the control center; If W i When <Y1, the temperature value Sz of the moment before the current moment is obtained, and the identification (W i -Sz) whether it satisfies: (W i -Sz)≥Y2, where Y2 is a preset value. If it is satisfied, a parameter reduction signal is generated and transmitted to the control center; Based on the determined parameter reduction signal, the control center reduces the charging parameter until the temperature parameter is reduced, and stops, and determines the reduced related parameter G, and controls the charging parameter to climb again, and the climbing value is (G-X1), where X1 is the preset value, and monitors whether the temperature exceeds the standard. If it exceeds the standard, it will be reduced again until the temperature drops, and then control the charging parameter to climb again (G-2X1). After multiple adjustments, it stops when the climbing temperature does not exceed the judgment standard: Record the charging parameter D1 before adjustment and the charging parameter D2 after adjustment, and use [D1, D2] as the optimal charging parameter interval for the charging pile in this working environment. The control center will then charge based on this optimal charging parameter interval and transmit this optimal charging parameter interval to the database for storage; The push center determines and displays the corresponding remaining charging time based on the determined optimal charging parameter range and the remaining capacity of the corresponding battery to be charged; The relevant data analysis end performs numerical analysis on the optimal charging parameter ranges at different stages stored in the database, determines the change curve of the relevant numerical values ​​based on the relevant changes in the maximum and minimum values, and performs a comprehensive analysis of the change curve to determine the relevant status of the charging pile.

2. The charging pile intelligent information push and management platform based on artificial intelligence according to claim 1 is characterized in that: If (W i -Sz) does not satisfy: (W i -Sz)≥Y2, continue monitoring.

3. The charging pile intelligent information push and management platform based on artificial intelligence according to claim 1 is characterized in that: The specific method for the push center to determine the remaining charging time includes: The confirmed remaining capacity to be charged is calibrated as R, and the fastest complete charging time T2 is determined based on R÷D2=T2, and the slowest complete charging time T1 is determined based on R÷D1=T1.

4. The charging pile intelligent information push and management platform based on artificial intelligence according to claim 1 is characterized in that: The database stores the optimal charging parameter intervals determined in different stages, and sorts the optimal charging parameter intervals according to the order of storage time.

5. The charging pile intelligent information push and management platform based on artificial intelligence according to claim 4 is characterized in that: The specific method of determining the change curve of the relevant value at the relevant data analysis end includes: The maximum and minimum values ​​of the corresponding optimal charging parameter ranges in different stages are arranged in chronological order, and a two-dimensional coordinate system is constructed with different stages as the horizontal coordinate axis and the corresponding charging parameters as the vertical coordinate axis. Then, the corresponding points in the coordinate system are determined with the different maximum and minimum values ​​corresponding to different stages, and the corresponding points are interconnected to determine their maximum value change curve and minimum value change curve.

6. The charging pile intelligent information push and management platform based on artificial intelligence according to claim 5 is characterized in that: The specific method of the relevant data analysis end for performing comprehensive analysis on the change curve includes: Determine the relevant vertical line of the corresponding points at the same stage between the two curves. The relevant vertical line is the connecting line of the corresponding points at the same stage. Determine the distance value of the relevant vertical line, which is calibrated as JL k , where k represents different stages, and the maximum value of the corresponding stage is marked as ZD k , the minimum value of the corresponding stage is marked as ZX k , where k = 1, 2, ..., n, and n represents the total number of the corresponding stages; Using HB j =(JL j -JL j-1 )+(ZD j -ZD j-1 )+(ZX j -ZX j-1 ) Determine the combined value HB j , where j∈(2,n), if the HB generated at different stages j <0, assign 1, if HB j When ≥0, assign a value of 2; Confirm the relevant assignments of several different stages in turn, and determine the proportion of assignment 1 ZB1 and the proportion of assignment 2 ZB2, where ZB1 = the total number of assignments 1 ÷ the total number of relevant assignments, and ZB2 = the total number of assignments 2 ÷ the total number of relevant assignments; If ZB1>2×ZB2, a status decline signal is generated and directly displayed in the management terminal of the administrator.

7. The charging pile intelligent information push and management platform based on artificial intelligence according to claim 6 is characterized in that: If the proportion ZB1 of the value 1 and the proportion ZB2 of the value 2 do not satisfy: ZB1>2×ZB2, no processing signal is generated.

Images